# Spontaneous Theory of Mind for Artificial Intelligence

arXiv: https://arxiv.org/abs/2402.13272 · HTML: https://mlsanity.com/paper/2402.13272/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 69 references that are in the map.
- First posted on arXiv 16 Feb 2024.

## Builds on (most cited first, 6 of 6)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Large Language Models Fail on Trivial Alterations to Theory-of-Mind Tasks](https://mlsanity.com/paper/2302.08399/) (2023)
- [Machine Theory of Mind](https://mlsanity.com/paper/1802.07740/) (2018)
- [Neural Theory-of-Mind? On the Limits of Social Intelligence in Large LMs](https://mlsanity.com/paper/2210.13312/) (2022)
- [Do Large Language Models know what humans know?](https://mlsanity.com/paper/2209.01515/) (2022)
- [Multiagent Inverse Reinforcement Learning via Theory of Mind Reasoning](https://mlsanity.com/paper/2302.10238/) (2023)

## Built on by (most cited first, 3 of 3)

- [Automated Meta Prompt Engineering for Alignment with the Theory of Mind](https://mlsanity.com/paper/2505.09024/) (2025)
- [The Theory of Mind Utility: A Formal Account of Mentalizing](https://mlsanity.com/paper/2606.12721/) (2026)
- [A Causal Model of Theory of Mind in Conflict for Artificial Intelligence](https://mlsanity.com/paper/2606.16944/) (2026)

## Abstract (arXiv)

Existing approaches to Theory of Mind (ToM) in Artificial Intelligence (AI) overemphasize prompted, or cue-based, ToM, which may limit our collective ability to develop Artificial Social Intelligence (ASI). Drawing from research in computer science, cognitive science, and related disciplines, we contrast prompted ToM with what we call spontaneous ToM -- reasoning about others' mental states that is grounded in unintentional, possibly uncontrollable cognitive functions. We argue for a principled approach to studying and developing AI ToM and suggest that a robust, or general, ASI will respond to prompts textitand spontaneously engage in social reasoning.